Agbogun, J. B. and Akpan, V. A. and Oluwade, B. A. and Yemi-Peters, V. I. (2019) A Prototype Machine Learning Algorithm and Its Possible Application to Information Extraction of Structured Academic Data from Unstructured Web Documents. 30 -43.
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Abstract
This paper proposes a machine learning approach for information extraction of structured academic data from unstructured web documents. The current challenges of information extraction have been critically examined as well as the state-of-the-art of structured data extraction. The proposed approach has been simplified and presented using a comprehensive flowchart. The proposed machine learning information extraction scheme is being validated using Kogi State University (KSU), Anyigba, Nigeria. The preliminary studies of KSU as well as an organogram of KSU are presented in the paper. The feasibility and realization of the proposed machine learning algorithm for information extraction of structured academic data from unstructured web documents have been justified and highlights on future directions have also been presented.
Item Type: | Article |
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Subjects: | Q Science > Q Science (General) |
Divisions: | Faculty of Natural and Applied Sciences |
Depositing User: | mrs chioma hannah |
Date Deposited: | 22 Nov 2022 10:09 |
Last Modified: | 22 Nov 2022 10:09 |
URI: | http://eprints.gouni.edu.ng/id/eprint/3914 |
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